PhD in Statistics – (Ph.D.)

Contents

The Program

The PhD in Statistics is designed for motivated students who wish to undertake research careers in Theoretical or Applied Statistics in academic or other institutions. MSc-level work in Economics, Statistics, Quantitative Social Sciences, Engineering, Mathematics or Physics will generally provide sufficient background for the doctoral program.During the first two years, students focus on coursework, while during the third and fourth year the PhD dissertation is the primary focus. During the first two years, students' academic program is monitored by the PhD program Director. Each student has to meet the Director at least once a quarter. Before presenting the Dissertation project (at the beginning of the Third Year), each student has to contact a potential Dissertation Advisor from the PhD Faculty.
The four-year plan is outlined as follows.

First Year

During the first year, students have to complete the six compulsory courses in a satisfactory way. Teaching is split into two semesters. All courses have 48 hours of lectures.
First Semester

• Real Analysis
• Statistics: Advanced Data Analysis
• Probability

Second Semester

• Statistical Theory
• Stochastic Processes
• Bayesian Statistical Theory

At the end of the first year students undertake a General Exam. The General Exam may be repeated only once.

Second Year

During the second year, students focus on courses concerning selected and/or advanced topics that have not been covered during the first year, as well courses concerning cognate disciplines. Before the beginning of the second year, students choose between two tracks: Theoretical Statistics or Applied Statistics. Along with a common core set of courses, according to the choice, students will follow a different set of courses. A student is expected to take at least nine courses during the year. Students present an individual Study Plan that has to be approved by the Faculty of the PhD. A set of courses is usually taught by Visiting Professors (Topics in Statistical Modelling, Topics in Theoretical Statistics, Topics in Applied Statistics). In specific cases, the Faculty can approve Study Plans that include courses taught outside Bocconi, especially when special agreements with other programs are present.

Common Core

Compulsory Courses

• Computational Statistics (24 hours)
• Mixture Models (24 hours)
• Time Series Analysis (24 hours)
• Topics in Statistical Modelling (14 hours)

Theoretical Statistics TrackIn this track, students are expected to specialize in advanced topics related to current directions in the methodology of Statistics. The study plan is as follows:
Compulsory courses

• Bayesian Non-parametric Inference (24 hours)
• Inference for Diffusion Processes (24 hours)
• Topics in Theoretical Statistics (14 hours)

Optional course

• Two other courses selected among all courses taught in the Ph.D. School, including courses taught for the Applied Statistics Track.

Applied Statistics Track In this track, students are expected to specialize in advanced topics related to current directions in the application of Statistics. Given the strength of Bocconi's PhD School and of the Faculty of the PhD in Statistics, an emphasis is put on Statistics as applied to Economics, Finance, Demography, Business Administration & Management.
Compulsory courses

• Econometrics I or Econometrics II (24 hours)
• Multilevel and Longitudinal Modelling (24 hours)
• Topics in Applied Statistics (14 hours)

Optional courses

• Two other courses are selected among all courses taught in the PhD School, including courses taught for the Theoretical Statistics track. At least one course has to be selected from those taught within the PhD in Business Administration & Management, Economics, or Finance. Courses that might be selected include, for example:
  • Courses from the Applied Studies in Managerial Research of the PhD in Business Administration & Management;
  • Courses from the Econometrics or Public Economics field of the PhD in Economics,
  • Courses from the Asset Pricing field of the PhD in Finance.

Third Year

During the third Year, students start working towards a PhD dissertation. The dissertation is the capstone of the PhD degree. It is expected to be an original piece of research of publishable quality. After discussing it with at least one advisor within the Faculty of the PhD in Statistics, students present a plan of their dissertation to the Faculty, usually during the month of September of the Third Year. The presentation is intended to demonstrate the viability of the topic for a dissertation and the students familiarity with the statistical issues related to the thesis. The Faculty has to approve the plan.
After the dissertation plan has been approved, students work towards the dissertation, under the supervision of at least one advisor. With the agreement of the advisor, students may spend periods outside Bocconi. At the end of the Third Year, the student presents a first research paper to the Faculty (Third Year Paper), usually during the month of June of the Third Year. The Third Year Paper has to be approved by at least two Faculty members.

Fourth Year

During the fourth Year, students are expected to complete their PhD dissertation. Students should present their work outside Bocconi as well, in seminars and/or conferences. In June, students present the main results in a seminar to the Faculty and they submit their dissertation to a Committee composed by at least three members (an internal advisor, an external member and at least one additional internal/or external member). The dissertation has to be considered acceptable by the Committee.
Subsequently, students have to discuss and obtain approval of the final version of their Doctoral dissertation with a discussion at Bocconi before the Thesis Committee nominated by the Rector.